Representación de formas digitales para reconocimiento y clasificación de objetos

En este trabajo se proponen e implementan herramientas de análisis de imágenes orientadas al desarrollo de algoritmos para reconocimiento y clasificación de objetos en imágenes digitales. El análisis se aplica a curvas que constituyen el borde de un objeto digital. Se propone una representación de formas planas basada en una aproximación poligonal de curvas, lo que reduce la cantidad de datos a manejar. Una silueta se representa con un patrón de curvatura que mide el cambio del vector tangente a lo largo del perímetro. Este patrón permite determinar características geométricas de la forma, como son concavidad, convexidad, puntos de inflexión, entre otros. Los puntos de inflexión se toman como puntos de referencia para dividir la curva en partes significativas. La identificación de objetos se realiza por comparación de patrones, de acuerdo a una métrica apropiada; que puede ser aplicada al patrón completo o a una o varias partes significativas. De esta manera se pueden medir similitudes entre formas de objetos en imágenes digitales, así como diferencias en ciertas partes significativas, permitiendo la clasificación de objetos del mismo tipo

Representation of digital forms for recognition and classification of objects

En este trabajo se proponen e implementan herramientas de análisis de imágenes orientadas al desarrollo de algoritmos para reconocimiento y clasificación de objetos en imágenes digitales. El análisis se aplica a curvas que constituyen el borde de un objeto digital. Se propone una representación de formas planas basada en una aproximación poligonal de curvas, lo que reduce la cantidad de datos a manejar. Una silueta se representa con un patrón de curvatura que mide el cambio del vector tangente a lo largo del perímetro. Este patrón permite determinar características geométricas de la forma, como son concavidad, convexidad, puntos de inflexión, entre otros. Los puntos de inflexión se toman como puntos de referencia para dividir la curva en partes significativas. La identificación de objetos se realiza por comparación de patrones, de acuerdo a una métrica apropiada; que puede ser aplicada al patrón completo o a una o varias partes significativas. De esta manera se pueden medir similitudes entre formas de objetos en imágenes digitales, así como diferencias en ciertas partes significativas, permitiendo la clasificación de objetos del mismo tipo.In this work, image analysis tools aimed at developing algorithms for object recognition and classification in digital images are proposed and implemented. The analysis is applied to curves that constitute the edge of a digital object. A representation of flat shapes based on a polygonal approximation of curves is proposed, which reduces the amount of data to be handled. A silhouette is represented by a curvature pattern that measures the change of the tangent vector along the perimeter. This pattern allows determining geometric characteristics of the shape, such as concavity, convexity, inflection points, among others. The inflection points are taken as reference points to divide the curve into significant parts. The identification of objects is carried out by comparing patterns, according to an appropriate metric; which can be applied to the entire pattern or to one or several significant parts. In this way, similarities between shapes of objects in digital images can be measured, as well as differences in certain significant parts, allowing the classification of objects of the same type

Thinning-free Polygonal Approximation of Thick Digital Curves Using Cellular Envelope

Since the inception of successful rasterization of curves and objects in the digital space, several algorithms have been proposed for approximating a given digital curve. All these algorithms, however, resort to thinning as preprocessing before approximating a digital curve with changing thickness. Described in this paper is a novel thinning-free algorithm for polygonal approximation of an arbitrarily thick digital curve, using the concept of "cellular envelope", which is newly introduced in this paper. The cellular envelope, defined as the smallest set of cells containing the given curve, and hence bounded by two tightest (inner and outer) isothetic polygons, is constructed using a combinatorial technique. This envelope, in turn, is analyzed to determine a polygonal approximation of the curve as a sequence of cells using certain attributes of digital straightness. Since a real-world curve=curve-shaped object with varying thickness, unexpected disconnectedness, noisy information, etc., is unsuitable for the existing algorithms on polygonal approximation, the curve is encapsulated by the cellular envelope to enable the polygonal approximation. Owing to the implicit Euclidean-free metrics and combinatorial properties prevailing in the cellular plane, implementation of the proposed algorithm involves primitive integer operations only, leading to fast execution of the algorithm. Experimental results that include output polygons for different values of the approximation parameter corresponding to several real-world digital curves, a couple of measures on the quality of approximation, comparative results related with two other well-referred algorithms, and CPU times, have been presented to demonstrate the elegance and efficacy of the proposed algorithm

Digital Image Processing

This book presents several recent advances that are related or fall under the umbrella of 'digital image processing', with the purpose of providing an insight into the possibilities offered by digital image processing algorithms in various fields. The presented mathematical algorithms are accompanied by graphical representations and illustrative examples for an enhanced readability. The chapters are written in a manner that allows even a reader with basic experience and knowledge in the digital image processing field to properly understand the presented algorithms. Concurrently, the structure of the information in this book is such that fellow scientists will be able to use it to push the development of the presented subjects even further